Service Conditions Research Articles

Time-domain expression and mechanical response of the viscoelastic Poisson's ratio in asphalt pavement

Poisson's ratio (PR) is a fundamental mechanical parameter for materials. Unlike the constant Elastic Poisson's Ratio (EPR), the Viscoelastic Poisson's Ratio (VEPR) is significantly influenced by external factors such as environmental temperature, stress level, and loading frequency. Using the VEPR to characterize the stress state of asphalt pavements provides a more accurate reflection of their actual service conditions. Moreover, the VEPR plays a more critical role than the EPR in predicting fatigue life, analyzing temperature sensitivity, and optimizing pavement structure design. In this study, the Elastic-Viscoelastic Correspondence Principle (EVCP) and the Zener mechanical model were combined to derive a time-domain expression for the VEPR of asphalt pavement. Fiber Bragg Grating (FBG) sensors were embedded within various structural layers of an in-service road to collect mechanical response and temperature data under traffic loads. Based on the measured temperature data, Finite Element Models (FEMs) were developed for both the VEPR and EPR conditions. The mechanical responses were validated using these FEMs, and the results were compared with the strain data collected by the FBG sensors. The results indicated that both VEPR and EPR increase most rapidly between 20°C and 35°C, with VEPR resulting in higher transverse and longitudinal strains and stresses than EPR, while vertical strain remained constant. Furthermore, the VEPR was better suited to actual driving conditions, with a peak error of only 3.97 % and an average error of 10.04 %.

Comparison of the effects of different ageing tests on flexural properties of flax fibre composites

This study investigates the changes in the flexural properties and microstructure of flax fibre thermoset composites induced by accelerated and natural ageing methods. The reductions in flexural strength and modulus of composites, ranging from 14 %–48 % and 6 %–57 %, respectively or even an increase in flexural properties after the cyclic ageing test, show the diverse effects of the tests on the flax composites. Only small differences in the composites' performance were found between the natural ageing under the shade and natural ageing exposed to sunlight. The long-term moisture cycling did not cause progressive damage; instead, the composite's flexural properties increased, likely due to an improvement in both the fibre's and matrix's mechanical properties. The water immersion test seems to be predictive of the long-term durability of uncoated flax composites in natural conditions. Microstructure analysis supports composites' flexural test results, with flax/epoxy showing superior properties compared to flax/polyester. The results suggest that uncoated flax composites can withstand extreme humidity changes, but perhaps not in applications wherein composites come in contact with liquid water for long periods, likely due to the effects of leaching. The varied impacts of the different ageing tests on flax fibre composites underscore the need to thoroughly select testing protocols that simulate service conditions relevant to the composites' intended application.

Understanding of the irradiation response of Cr-based ATF coatings using in-situ TEM

Although CrNb coated zirconium alloy materials are considered as ATF candidates with excellent oxidation resistance and mechanical properties, the irradiation response behavior under harsh and complex service conditions is still unrevealed. Here, we report the evolution of the microstructure of pure Cr and CrNb coatings with different Nb contents under simultaneous irradiation with Cr+-He+-H2+ triple ion beams at 633 K by using an advanced in-situ transmission electron microscope (TEM). The results show that CrNb coatings with high Nb content have better irradiation stability. Under high-temperature irradiation conditions, irradiation-induced oxidation and grain growth or crystallization are observed for both Cr-8 Nb with a nanocrystalline structure and Cr-18 Nb coatings with an almost amorphous structure, whereas Cr-37 Nb coatings maintains relatively intact in the amorphous phase after irradiation at a dose of 10 dpa. Based on the in-situ tracking of the microstructural evolution, it is revealed that the mechanism of irradiation-accelerated oxidation and crystallization of coatings originates from displacement cascades enhancing local atomic diffusion and rearrangement.

Mild Traumatic Brain Injury in U.S. Military Veterans: Results from the National Health and Resilience in Veterans Study

Objective This study provides nationally representative data on the prevalence, risk factors, and associated mental health and functional outcomes of mild traumatic brain injury (mTBI) in U.S. military veterans. Methods Data (N = 4,069) were analyzed from the National Health and Resilience in Veterans Study (NHRVS). Analyses estimated mTBI prevalence, exposure to different mTBI injuries, and past-week mTBI symptoms (i.e. persistent post-concussive symptoms [PCS]). Comparisons were made between veterans with and without mTBI+PCS on sociodemographic, military, trauma, and psychiatric characteristics. Associations between mTBI+PCS and measures of cognitive, mental, and psychosocial functioning were examined. Results Overall, 43.7% endorsed a possible mTBI event on the Veterans Affairs’ Mild TBI Injury Screening and Evaluation tool, and 10.0% screened positive for mTBI. After combining a self-reported healthcare professional diagnosis of concussion/mTBI/TBI (5.8%) with a positive mTBI screen, the prevalence of mTBI+PCS was 3.0%. Veterans with specific trauma characteristics (e.g. adverse childhood events), military service (e.g. combat), and lifetime psychiatric conditions were more likely to have mTBI+PCS. mTBI+PCS was associated with increased odds of current posttraumatic stress disorder, major depressive disorder, generalized anxiety disorder, and drug use disorder. These veterans also scored significantly lower on cognitive, mental, and psychosocial functioning. Conclusions Overall, 3.0% of veterans had mTBI+PCS, suggesting that while mTBI may be prevalent in this population, the majority will likely recover without developing chronic symptoms. Those with mTBI+PCS are at significant risk for comorbid psychiatric diagnoses and poorer psychosocial functioning relative to those without mTBI+PCS, and early targeted identification may assist in prevention of disability and recovery.

Accounting for taxi service conditions in estimating route travel time from floating car data using Markov chain model

Recognising the variations in driving behaviour between taxis in the empty and carry conditions is pivotal for enhancing the accuracy of route travel time estimations using floating car data. However, existing methods largely overlook this distinction. In light of this, this study aims to harness these variations for more precise estimations. Utilising taxi data, we segmented the information by service conditions and executed distinct estimations for each segment. The route travel time was deduced through convolutional operation, complemented by a Markov chain model to discern correlations between travel times across various links. Our innovative approach realised a substantial enhancement in accuracy. Notably, when accounting for distinct service conditions, there was a reduction of 51.44% in mean absolute error and a 46.83% decline in maximum percentage error. By providing more accurate and reliable travel time predictions, our methodology enables better-informed traffic management decisions. Accurate travel time estimations are essential for optimising traffic signal timings, planning efficient routing strategies, and managing road network usage. These improvements in traffic management can lead to smoother traffic flow, reduced travel times, and ultimately, diminished congestion in urban areas.

Investigation on mechanical and tribological properties of PTFE nanocomposites reinforced by surface-modified graphene using molecular dynamics simulations

Surface-modified nanoparticles are commonly used to improve the mechanical properties and wear resistance of polytetrafluoroethylene (PTFE). However, fewer studies have been devoted to quantitatively revealing the action mechanism of graphene (Gr) modified with different functional groups on the mechanical and tribological properties of PTFE. Herein, the effects of four functional groups (−OH, −NH2, −COOH, and −COOCH3 functional groups) on the surface of Gr nanosheets on the mechanical and tribological properties of PTFE nanocomposites are studied using molecular dynamics simulations. The results indicate that the incorporation of functional groups to the Gr surface is able to significantly improve the mechanical properties and wear resistance of the nanocomposites, and the COOH-functionalized Gr nanosheet shows the best reinforcing effect due to the synergistic effect of its own high surface roughness and strong interfacial interaction between itself and the matrix. It is also found that the friction coefficient of the nanocomposites is obviously increased by the inclusion of functionalized Gr nanosheets, and the greater the surface roughness of the functionalized Gr nanosheet, the more significant the growth of the friction coefficient of the nanocomposites. The pull-out test and confined shear simulation reveal that due to the increased interfacial shear strength and the isolation of functional groups, an inhomogeneous transfer film is formed at the friction interface, leading to a decreased anti-friction property. This study provides some guidance for the future design and development of polymer nanocomposites with excellent mechanical and tribological performance for use in extreme service conditions.

Insight into microstructure evolution of in-situ ZrB2np/AA6111 composites with both excellent room and high temperature properties

With rapid development of aerospace and automobile, the service condition of structural components becomes increasingly harsh, diverse and high mechanical properties are urgently needed. In this work, an advanced in-situ ZrB2np/AA6111 composite with excellent room and high-temperature properties was prepared via Al-Zr-B reaction system. The microstructure revealed that ZrB2 nanoparticles with regular polygonal shapes ranged from 10 to 150 nm approximately, and a good α-Al/ZrB2 interface bonding was confirmed. The agglomeration of ZrB2 particles was significantly weakened during hot extrusion. Due to the inhibiting effect on dislocation motion and pinning effect on grain boundaries induced by ZrB2 particles, fine recrystallized grains were obtained in ZrB2/AA6111 composites after extrusion. Compared with AA6111 matrix alloy, the yield strength, ultimate tensile strength and elongation of AA6111-3ZrB2 composites at room temperature and 300 °C were increased by 18.9 %, 12.7 %, 50.0 % and 34.1 %, 22.4 %, 42.4 %, respectively. An excellent room and high-temperature strengthening effect was simultaneously achieved assisted by ZrB2 particles. The improvement of room-temperature properties was mainly owed to the Grain refinement and Orowan bypassing strengthening mechanisms. The good high-temperature properties mainly relied on the superior coarsening resistance of ZrB2 particles which could fully played the Orowan strengthening effect and well protected the grain boundaries at high temperature. This work provides a feasible approach to design high-performance aluminum alloys and is beneficial for the further development of modern industries.

Evolution Characteristics of Aluminum Thermal Weld Irregularity and Damage in Heavy-Haul Railway under Different Service Conditions

Aluminum thermal welding joints are widely used in the maintenance welding of heavy-haul railways due to their easy handling and high efficiency. However, due to their inherent welding characteristics, welding results in certain differences in the material’s physical properties at the welding zone compared to adjacent base materials, leading to the occurrence of short-wave irregularity under long-term wheel–rail interactive forces. In order to explore the evolution characteristics of weld irregularity, dynamic characteristics, and plastic deformation under long-term wheel–rail impact, a detailed tracking test was conducted on a normal aluminum weld, and the process from being put on the track to being damaged and replaced was evaluated. At the same time, a rigid–flexible coupling model was established for subsequent analysis, and plastic damage was analyzed using the finite element model. The results show that the service life of the weld can be divided into three different stages: the initial stage, the intermediate stage, and the damage stage. In the damage stage, a temporary separation occurred between the wheel and rail, leading to a sudden change in the wheel–rail interaction. The weight of 250 MT at the weld reached the repairment control limit. The concentration effect of equivalent plastic deformation was most serious at 2~5 mm below the rail head.

Review of aging mechanisms, mechanical properties, and prediction models of fiber‐reinforced composites in natural environments

AbstractFiber‐reinforced composites are widely used in civil engineering, aerospace, automotive, and medical sectors. However, these composites undergo aging due to factors such as temperature, humidity, load, and so on, during their usage. As a result, their performance deteriorates, and predicting their durability under real service conditions is a significant challenge. In order to better understand the durability of fiber‐reinforced composites, this article summarizes their microscopic aging mechanism under natural aging conditions and analyzes the changing rules of tensile, bending, and shear properties of composites under seven typical climate types, including tropical desert climate, temperate continental climate, temperate oceanic climate, Mediterranean climate, seasonal climate, tropical rainforest climate, and seawater immersion. This article reviews various durability prediction models, such as the Arrhenius model, prediction models based on residual modulus of elasticity and residual strength, and median strength regression analysis. To enhance the accuracy of aging life prediction during the natural aging process of composites, it is important to consider the influence of loads under real service conditions, incorporate different climatic types, utilize comprehensive mechanical property indices, establish an equivalent conversion relationship between natural aging and accelerated aging, and create a database with unified test standards.Highlights The aging mechanisms of FRP after exposure in natural aging environments are discussed. The tensile, bending, and shear properties of FRP after exposure under seven climate types are discussed. The predictive models are proposed for the FRP used in natural aging. The future research needs are proposed for the FRP used in natural aging.

Effects of TiAlN Coating Thickness on Machined Surface Roughness, Surface Residual Stresses, and Fatigue Life in Turning Inconel 718

The surface roughness and surface residual stresses are affected by the coating thickness of physical vapor deposition (PVD) TiAlN tools, which could alter the service performance of machined components. However, the relationships among the tool coating thickness, the machined surface roughness, the surface residual stress, and the fatigue life are still not sufficiently illustrated. In this research, PVD TiAlN coatings with several thicknesses of 1.6 μm, 2 μm, 2.5 μm, and 3 μm were deposited on carbide tools. Turning experiments using Inconel 718 were conducted with uncoated and various TiAlN tools under flood cooling conditions. The surface roughness could be improved with the selection of thin PVD TiAlN coating thicknesses of 1.6 μm and 2 μm compared to that of uncoated tools. The tensile residual stresses at the machined surface in the directions of cutting speed and feed rate linearly decreased by 148.67% and exponentially decreased by 92.24% when the TiAlN coating thickness was increased from 0 μm to 3 μm. The values of the low-cycle fatigue life of machined Inconel 718 linearly increased by 15.60% with the increase in TiAlN coating thickness from 0 μm to 3 μm, which was mainly due to the improvement of surface residual stresses. The results could provide guidance for the selection of suitable TiAlN coating thicknesses for wet machining Inconel 718 based on the part service conditions.

Comparative study of intergranular acicular nano-precipitate evolution and their effects on creep failure behavior for BM and HAZ in a novel Fe-Ni-based alloy joint

Intergranular acicular nano-precipitate evolution and their effects on creep failure behavior for the base metal (BM) and heat affected zone (HAZ) in a novel cost-effective Fe-Ni-based alloy joint were investigated comparatively. It was found that the BM tended to initiate acicular nano-precipitates perpendicular to grain boundaries, while their formation was suppressed at the HAZ. After creep at 650 °C under 300 MPa, nano-precipitates composed of γ´-Ni3(Al, Ti), M23C6 and σ phase at BM would expand along the grain boundaries (GBs) with significant GB migration. Creep cavities were more prone to initiate at the precipitate-free zone and the acicular nano-precipitate roots due to the precipitation strengthening reduction and local strength mismatch. Furthermore, grain boundary embrittlement induced by acicular precipitates and the presence of recrystallized grains at the crack tip also promoted the crack propagation. In contrast, the welding thermal cycle contributed to the M23C6 redistribution at the GBs, which decreased element diffusion rate and dragging grain boundary movement, thereby exhibiting better creep crack resistance at the HAZ. The finding provided profound implications for the comprehensive understanding of acicular nano-precipitate evolution in the newly designed Fe-Ni-based alloy joint under service condition.

A novel approach for damage assessment in adhesively bonded composite joints using backface strain technique

In this study, the backface strain (BFS) is measured by both digital image correlation (DIC) and fiber optic sensors (FOS) to detect the crack initiation and propagation in adhesively bonded composite single-lap joints (SLJ). BFS measures the resultant strain deriving from the positive strain, due to tensile load, and negative strain related to the bending moment. A point, called zero-strain point (ZSP), can be detected on the substrate surface of SLJ due to the concurrent effect of these positive and negative strains. The experimental activity shows that the value of the ZSP changes when the crack starts to propagate. Thus, this point can be used to monitor the service conditions of adhesive joints. The effect of joint dimensions on the position of the ZSP is investigated when the joint is subjected to quasi-static loading. In addition, the applicability of the method is investigated under a cyclic loading condition. The work shows that the ZSP can be used as an index to monitor joint healthiness. Furthermore, FOSs can be used for an in-situ monitoring of the joint.

Full-scale polymer relaxation induced by single-chain confinement enhances mechanical stability of nanocomposites

Polymer nanocomposites with tuning functions are exciting candidates for various applications, and most current research has focused on static mechanical reinforcement. Actually, under service conditions of complex dynamic interference, stable dynamic mechanical properties with high energy dissipation become more critical. However, nanocomposites often exhibit a trade-off between static and dynamic mechanics, because of their contradictory underlying physics between chain crosslinking and chain relaxation. Here, we report a general strategy for constructing ultra-stable dynamic mechanical complex fluid nanocomposites with high energy dissipation by infusing complex fluids into the nanoconfined space. The key is to tailor full-scale polymer dynamics across an exceptionally broad timescale by single-chain confinement. These materials exhibit stable storage modulus (100 ~ 102 MPa) with high energy dissipation (loss factor > 0.4) over a broad frequency range (10−1 ~ 107 Hz)/temperature range (−35 ~ 85°C). In the loss factor > 0.4 region, their dynamic mechanical stability (rate of modulus change versus temperature (k)) is 10 times higher than that of conventional polymer nanocomposites.

Superalloys fracture process inference based on overlap analysis of 3D models

Superalloy materials exhibit susceptibility to fracture failures stemming from the influence of thermomechanical factors. To comprehensively understand the fracture mechanisms, material properties, root causes of failure, and the subsequent optimization of alloys, a detailed analysis of the internal fracture process and the morphological traits of the fracture surface is imperative. Traditional analysis of fracture surfaces solely relies on 2D images, thus lacking crucial 3D information. Although in situ experiments can capture the fracture process, their effectiveness is confined to the specimen’s surface, precluding insight into internal changes. Here we introduce an integrated framework encompassing the process of 3D reconstruction of fracture surfaces, aiming to enhance the visual information obtained with micron-level accuracy, visual intuitiveness and sense of depth. Additionally, this framework also facilitates the scrutiny and inference of internal fracture processes. These results demonstrate that under specific service conditions, material deformation fracture probably stems from a combination of surface cracking and internal cracking rather than exclusively one or the other. Overall, our description and analysis of internally initiated cracking due to defects within the specimens can be beneficial in guiding future alloy design and optimization efforts.

Five years in the community dental service: clinicians' perspectives.

Introduction Community dentists in England treat patients classed as vulnerable. The services in which they operate have faced challenges, with these known to have affected clinicians. It is important to monitor and understand the workforce and the effect the healthcare landscape, and its changes, has on them and the service they provide.Aims To explore and describe the evolution of working conditions of community dental service (CDS) dentists in England.Materials and methods Data for a cohort of dentists working in the CDS in England between 2017 and 2022, collected via questionnaire, were statistically and thematically analysed and data compared.Results Motivation in clinicians working in the service has significantly fallen since 2017 and concerns were held over the service meeting patient need. CDS dentists have become increasingly satisfied with the care they provide, though workload and job stress increased. Satisfaction with job terms and conditions increased significantly, though job satisfaction, with high and low morale, decreased over the period of interest. Working conditions and motivation were described as deteriorating, alongside increasing satisfaction with job terms and conditions, and fewer dentists reporting low morale. Factors cited as contributing to lower job satisfaction and morale were staffing, workload and working conditions.Conclusions We suggest that despite the increased pressures on the CDS, little improvement has been made to working conditions. The working environment continues to erode for CDS dentists in England and patient service is being negatively affected. While dentists appear to have adapted to these conditions, it is imperative that attention is paid both to CDS dentists and the service and improvements made.

A Performance Evaluation Method for Long and Steep Uphill Sections of Heavy-Haul Railway Lines

Any system for evaluating the safety service performance of heavy-haul railway lines must effectively reflect the real-time service status of the line. The working conditions of heavy-load lines are complex and diverse, particularly on uphill sections. Existing evaluation systems struggle to accurately reflect the service conditions of long and steep uphill sections bearing heavy loads, posing a significant threat to the safe operation of these lines. To address this problem, we propose a new method for evaluating the safety service performance of long and steep uphill sections of heavy-haul railway lines by establishing a scoring system based on the Analytic Hierarchy Process (AHP). First, damage indicators for heavy-haul lines are categorized into three groups: track geometry status indicators, track structure status indicators, and track traffic status indicators. Using data from existing heavy-haul lines and maintenance experiences, we determine a score deduction standard, classifying lines into four levels based on their safety service quality. Next, we establish a coefficient table for the service performance of long and steep uphill sections after the corresponding scores are deducted. Using data for the length and elevation grade of the actual uphill section, we adjust the deducted scores of the track structure status indicators, enhancing the evaluation system’s accuracy in describing the working conditions. Finally, we verify the stability of the entire system by conducting a sensitivity analysis of the indicator evaluation results using the One-At-a-Time (OAT) method. This method fills a critical gap in the safe operation and maintenance of heavy-haul railways and provides a safety guarantee for the operation of long uphill sections of heavy-haul railways.

Prediction of crack plane orientation in railway wheels for different braking conditions

In this paper the stress analysis of a railway wheel is introduced. The wheel was analysed by Finite element method (FEM) under different service conditions during the braking process, which means that the friction coefficient and the relative speed between the wheel and rail were altered, creating 22 different loading conditions. Stress and strain histories were evaluated in the time domain during rolling, and the fatigue parameter was used to find the critical plane in each condition. The orientation of this critical plane was used to predict the crack propagation direction and the possible fatigue mode of the wheel. Relying on the results a critical plane map was created to visualize the possible fracture modes of the wheel under different loading conditions.

Fatigue Crack Monitoring Method Based on the Lamb Wave Damage Index.

For practical engineering structures, fatigue is one of the main factors affecting their safety and durability. Under long-term service conditions, the minor damage will be affected by fatigue loading and expand to macroscopic cracks, affecting the structure's service performance. Based on the sensitivity of Lamb waves to minor and initial damage, a damage monitoring method for fatigue crack propagation is proposed. By carrying out fatigue crack propagation tests under constant amplitude loading, the Paris equation of 316L steel and damage signals at different crack growth stages were obtained. Combined with damage monitoring tests and finite element analysis, the relationship between the phase damage index (PDI), amplitude damage index (ADI), signal correlation coefficient, and fatigue crack propagation length was studied. Compared with PDI and ADI, the signal correlation coefficient is more sensitive to crack initiation, which can be selected as the damage monitoring index in the initial stage of crack growth. With the increase of fatigue crack propagation length, the peak time of the direct wave signal gradually moves backward, which shows an obvious phase change. In the whole fatigue crack growth stage, PDI and crack length show a monotonically changing trend. By using the stress intensity factor as the conversion parameter, a prediction model of the fatigue crack propagation rate based on PDI was established. Compared to the fatigue crack propagation rate measured by experiments, the relative error of the predicted results is 10%, which verifies the accuracy of the proposed damage monitoring method.

Crystal plasticity finite element simulations on extruded Mg-10Gd rod with texture gradient

The mechanical properties of an extruded Mg-10Gd sample, specifically designed for vascular stents, are crucial for predicting its behavior under service conditions. Achieving homogeneous stresses in the hoop direction, essential for characterizing vascular stents, poses challenges in experimental testing based on standard specimens featuring a reduced cross section. This study utilizes an elasto-visco-plastic self-consistent polycrystal model (ΔEVPSC) with the predominant twinning reorientation (PTR) scheme as a numerical tool, offering an alternative to mechanical testing. For verification, various mechanical experiments, such as uniaxial tension, compression, notched-bar tension, three-point bending, and C-ring compression tests, were conducted. The resulting force vs. displacement curves and textures were then compared with those based on the ΔEVPSC model. The computational model's significance is highlighted by simulation results demonstrating that the differential hardening along with a weak strength differential effect observed in the Mg-10Gd sample is a result of the interplay between micromechanical deformation mechanisms and deformation-induced texture evolution. Furthermore, the study highlights that incorporating the axisymmetric texture from the as-received material incorporating the measured texture gradient significantly improves predictive accuracy on the strength in the hoop direction. Ultimately, the findings suggest that the ΔEVPSC model can effectively predict the mechanical behavior resulting from loading scenarios that are impossible to realize experimentally, emphasizing its valuable contribution as a digital twin.

Investigation on the thermal characteristics of electronic system and prediction of chip temperature by machine learning

In this work, the thermal characteristics and steady-state temperatures (SST) of CPU and FPGA of electronic system in nuclear power plant are explored. Finite element analysis is performed to simulate the test process. Furthermore, three machine learning algorithms are used to predict chips temperatures at different operating conditions. It is found that when the ambient temperature is 20 °C and all the fans are power-off, the SST of the CPU and FPGA reaches 75 °C and 72 °C, respectively. While when the fans are power-on, the SST of the CPU and FPGA drops to 37.5 °C and 33 °C. When the ambient temperature increases to 55 °C and all the fans are power-on, the SST of the CPU and FPGA is 72.3 °C and 68.2 °C, respectively. The finite element model is verified and used to generate test data. Three machine learning models are verified by predicting the SST of CPU and FPGA under different operating conditions. It is found that M-SVR has better prediction ability than DT and ANN. The findings can be used for chip reliability evaluation of other electronic system devices, and provide a new method for predicting the possible steady-state temperature of chips under different service conditions.